Radio resource scheduling with deep pointer networks and reinforcement learning
This article presents an artificial intelligence (AI) adaptable solution to handle the radio
resource scheduling (RRS) task in 5G networks. RRS is one of the core tasks in radio …
resource scheduling (RRS) task in 5G networks. RRS is one of the core tasks in radio …
Radio resource scheduling for 5G NR via deep deterministic policy gradient
SC Tseng, ZW Liu, YC Chou… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
The fifth generation (5G) wireless system plays a crucial role to realize future network
applications with diverse services requirements. The 3rd Generation Partnership Project …
applications with diverse services requirements. The 3rd Generation Partnership Project …
Learn to schedule (LEASCH): A deep reinforcement learning approach for radio resource scheduling in the 5G MAC layer
Network management tools are usually inherited from one generation to another. This was
successful since these tools have been kept in check and updated regularly to fit new …
successful since these tools have been kept in check and updated regularly to fit new …
Deep reinforcement learning for radio resource allocation and management in next generation heterogeneous wireless networks: A survey
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Autonomous radio resource provisioning in Multi-WAT private 5G RANs based on DRL
L Chinchilla-Romero, J Prados-Garzon… - 2023 IEEE Wireless …, 2023 - ieeexplore.ieee.org
Multi-Wireless Access Technology (WAT) Radio Access Networks (RANs) are becoming a
key enabler in 5G and beyond networks due to the public spectrum scarcity, the level of …
key enabler in 5G and beyond networks due to the public spectrum scarcity, the level of …
Deep reinforcement learning for scheduling in cellular networks
Integrating artificial intelligence (AI) into wireless networks has drawn significant interest in
both industry and academia. A common solution is to replace partial or even all modules in …
both industry and academia. A common solution is to replace partial or even all modules in …
Optimal radio resource management in 5G NR featuring network slicing
Abstract 3GPP 5G New Radio (NR) has introduced several new features that the network
slicing concept can leverage to guarantee the heterogeneous requirements in terms of …
slicing concept can leverage to guarantee the heterogeneous requirements in terms of …
DDPG-based radio resource management for user interactive mobile edge networks
PC Chen, YC Chen, WH Huang… - 2020 2nd 6G …, 2020 - ieeexplore.ieee.org
The development of the fifth-generation (5G) system on capability and flexibility enables
emerging applications with stringent requirements, such as ultra-high-resolution video …
emerging applications with stringent requirements, such as ultra-high-resolution video …
When multiple agents learn to schedule: A distributed radio resource management framework
Interference among concurrent transmissions in a wireless network is a key factor limiting
the system performance. One way to alleviate this problem is to manage the radio resources …
the system performance. One way to alleviate this problem is to manage the radio resources …
AI-based radio resource allocation in support of the massive heterogeneity of 6G networks
There is a consensus in industry and academia that 6G wireless networks will incorporate
massive heterogeneous radio access technologies (RATs) in order to cater to the high …
massive heterogeneous radio access technologies (RATs) in order to cater to the high …